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THE IMPACT OF THE RECENT FEDERAL RESERVE LARGE-SCALE ASSET
PURCHASES ON THE AGRICULTURAL COMMODITY PRICES: A HISTORICAL
Title DECOMPOSITION
of Research Project
Researcher’s
Name
Sayed H. Saghaian and Michael R. Reed
Department(s), University of Kentucky, Lexington, KY
Department of Agricultural Economics, University of Kentucky, Lexington, KY
Introduction
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After the Great Recession of 2007/2009, the U.S. Federal Reserve has
followed unprecedented expansionary monetary policies in order to
stimulate the economy, stabilize financial markets, and restore confidence
in the economy.
The Fed implemented policy of purchasing large amounts of assets to get
liquidity into the economy. This policy is called quantitative easing (QE). In
this study, we evaluate the effects of the recent Fed’s large-scale asset
purchases(LASPs) on prices of agricultural commodities.
The first LASP was announced at the end of 2008, and the second LASP
was announced in November of 2010.
Data Description
Monthly dataset from Jan 2000 to July 2013
Meats:
Beef - USDA Market News
Pork- index mundi (courtesy of IMF)
Broiler- USDA ERS (sales-weighted average of whole chicken prices and chicken part
prices).
Cereal Grains :
Corn, soybeans, wheat and rice price data are from the USDA Economic Research
Service.
Softs:
Sugar - index mundi (courtesy of the World Bank)
Cocoa - index mundi (courtesy of the International Cocoa Organization)
Coffee - International Coffee Organization
Cotton - USDA market news.
Figures 3 shows the historical decomposition graphs of the agricultural commodity
prices under investigation for a seven–month time horizon, using RATS software. The
left column shows the results for QE1 in 2008-2009, and the right column shows those
for QE2 in 2010-2011.
The solid lines are the actual prices including the impact of the LSAPs.
The dashed lines are the predicted prices excluding the effects of the LSAPs.
Cereal Grain:
Corn
Empirical Method
An historical decomposition analysis is used to estimate the dynamic short-run effects of
the two LSAP announcements on each commodity price over a seven-month time horizon
after each event.
Historical decomposition graphs measure the magnitude of price transmission due to the
QEs. These decomposition functions track the evolution of LSAPs through the system and
trace forecasted prices in the absence of LSAP versus actual prices which include the
effects of LSAPs. Comparing the forecasted prices without LSAP with the actual prices
provides an estimate of LSAP effects.
Figure 1. Prices of Cereal Grains: Corn,
Soybeans, Rice, and Wheat, 2000:01-2012:12
Figure 2. Prices of Meats: Beef, Broiler, and Pork,
2000:01-2012:12
Figures 1 and 2 show that agricultural prices have seen great volatility since
December 2008 and it is not clear that monetary policy and QE has had no
inflationary impacts, at least with respect to agricultural commodities.
Agricultural prices are particularly sensitive to monetary policy because they
are more flexible than manufactured good or service prices. Many of them are
storable and subject to large fluctuations due to weather and demand shocks.
Their demand and supply elasticities are small in absolute value. So it is very
difficult to distinguish short-run price changes from longer-run inflationary
tendencies.
Objective
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The objective of this study is to investigate the impacts of recent monetary
policy LSAPs on short-run agricultural commodity prices.
No study has investigated the effects of both LSAPs on agricultural prices,
though there has been a long history of empirical analyses of monetary
policy on commodity prices.
The commodities included in this analysis are:
meats (beef, pork, and broilers)
cereal grains (corn, soybeans, wheat, and rice)
softs (sugar, coffee, cocoa, and cotton).
Historical decomposition graphs are based on partitioning the moving average series into
two parts:
where is the multivariate stochastic process for an agricultural price, is its multivariate noise
process, is the deterministic part of and s is a counter for the number of time periods (RATS
software 2006, Fackler and McMillin 2002). The first sum represents that part of due to
innovations that drive the joint behavior of commodity prices for period to , the horizon of
interest. The second part is the forecasted price series based on information available at
time t, the date of an event (in this case the LASP) -- that is, how prices would have evolved
if there had been no changes (RATS 2006).
Empirical Results
 The historical decomposition results show that QEs impacted commodity prices
differently:
The effects of QE1 on the prices in 2008-2009 show very little positive impact of the QE for
most agricultural commodities. The actual commodity prices (the solid lines) that include
the impact of the QE are below or very close to the dashed lines for most commodities.
The historical decomposition graphs for QE2 in 2010-2011 tell a very different story. The
historical decomposition graphs in the right column of figure 3 see a jump in actual prices
(solid lines) of ten out of twelve agricultural commodities under investigation. Only wheat
and broilers were not positively influenced by QE2.
Soft:
Sugar
Meat:
Beef
Figure 3: The Effects of the Recent Federal Reserve’s Purchases of Long-Term Assets on Prices of Agricultural
Commodities.
Conclusions
 Overall the two LSAPs events had different impacts on the commodity prices under
investigation. The impacts of those announcements depend on the state of the economy at
the time, the characteristics of the products, as well as perceptions of risks associated with
the expansionary policy actions.
 With QE1 most prices were unaffected or fell with the announcement, while QE2 had just
the opposite impact. With QE2, actual prices (solid lines that include the impact of the
LSAP) were all higher (except for broilers and wheat) than forecast prices (dashed lines
that exclude the effects), and the forecast prices did not get close to actual prices during
the seven-month time horizon considered in this study.
 The conclusion from this study is that the new monetary policy changes can have important
effects to agricultural commodity prices and can cause wide swings.